Utilizing Discharge Flow Measurements to Estimate Continental-Scale Hydraulic Resistance and Channel Geometry

Abstract:

With the advent of hydrologic models capable of simulations over continental scales, such as NOAA’s operational National Water Model (NWM), accurately estimating the hydraulic parameters covering these large and diverse areas is not straightforward, primarily due to the lack of available datasets. In particular, hydraulic resistance is a difficult parameter to estimate and is often assumed a priori without suitable calibration or validation. The questions that this project addresses are fundamental to hydrologic modeling and prediction: What dimensions do rivers have and what is their hydraulic resistance? What degree of predictive improvement can be expected by improving reach properties in a continental-scale model such as the NWM?

In this effort, we improve the reach values of channel dimensions and hydraulic resistance contained within the database of ~2.7 million reaches utilized by the NWM. To do this, we utilize a new large dataset of ~3.1 million empirical discharge flow measurements (width, depth, velocity) from ~48,000 gages compiled from USGS and eight states. From this initial dataset, we calculate hydraulic geometry to populate the reach channel dimensions and calculate the reach-scale hydraulic resistance in combination with longitudinal slope. The updated static channel reach database is evaluated against the most-current NWM version (v2.1) first at twelve regional NWM test locations and the full CONUS NWM. The results of this effort suggest that hydraulic resistance shows a strong relationship with slope, and is one of the most sensitive of all in-channel properties. For the NWM, the relative effect of improved hydraulic resistance depends on the organization of the stream network and the size of the watershed, but tends to improve predictions primarily for short-term flow events.

The end result of the present effort will support more accurate predictive performance of the NWM, and may help to resolve errors originating in other parts of the model framework as well as improving the channel component of other large-scale CONUS hydrologic models. In addition, the strong empirical relationship between slope and hydraulic resistance spans four orders of parameter space and is a key advance for improving the remote sensing of discharge. This work was supported by NOAA through funding from NOAA-OAR-OWAQ-2018-2005496.